Recently, I came across something new while going through KodeKloud’s Free AI Week — a tool called Qwen AI. I had heard of ChatGPT and Gemini before, but Qwen feels a little different, especially when it comes to working with Kubernetes.
I’m still exploring it, but my first impression has been interesting.
What Makes Qwen Different
Unlike ChatGPT or Gemini, which you interact with on the web, Qwen AI actually runs inside your Kubernetes cluster. That means it doesn’t just give generic advice — it can directly access your cluster through the CLI. You can ask questions about your pods, deployments, or errors, and it will check the live state of your cluster before responding.
This is a big difference compared to other AI tools. With ChatGPT or Gemini, you usually copy-paste errors or YAML files and then wait for suggestions. Qwen, on the other hand, feels like having a smart assistant right inside your terminal.
My Experience So Far
The part that stood out to me is how natural it feels:
You type your question in your shell.
Qwen reads the context from your cluster.
It suggests fixes or points out where the issue might be.
It’s like combining kubectl commands with an AI brain, without switching windows or looking up docs every time.
Another thing I noticed — it’s secure. Since Qwen is installed inside the cluster, no data is leaving your environment. That’s a relief, especially for people working in companies where sending logs or configs outside is not allowed.
Why This Matters
Kubernetes troubleshooting is often about trial and error — running kubectl get pods, checking logs, trying different fixes. Having Qwen sitting inside the cluster can cut down that time by directly pointing out what’s wrong.
For me, it feels like a blend of a teammate + command line tool. Instead of just guessing or searching on the web, I can get context-aware help right where the problem exists.
What’s Next
I’m still learning and experimenting with Qwen AI, so this is just my early take. I’ll post more updates as I go deeper and try it on different use cases.
But one thing is clear — tools like Qwen are showing us a new way of working with Kubernetes. It’s not just about having AI answer questions, it’s about having AI inside the system, ready to troubleshoot with you.